add friendly deprecation message (#81)

test/test_transforms.py

@@ -150,7 +150,8 @@ class Tester(unittest.TestCase):
         self.assertTrue(mel_transform.fm.fb.sum(1).le(1.).all())
         self.assertTrue(mel_transform.fm.fb.sum(1).ge(0.).all())
         # check options
-        mel_transform2 = transforms.MelSpectrogram(window=torch.hamming_window, pad=10, ws=500, hop=125, n_fft=800, n_mels=50)
+        kwargs = {"window": torch.hamming_window, "pad": 10, "ws": 500, "hop": 125, "n_fft": 800, "n_mels": 50}
+        mel_transform2 = transforms.MelSpectrogram(**kwargs)
         spectrogram2_torch = mel_transform2(audio_scaled)  # (1, 506, 50)
         self.assertTrue(spectrogram2_torch.dim() == 3)
         self.assertTrue(spectrogram2_torch.le(0.).all())

torchaudio/transforms.py

 from __future__ import division, print_function
+from warnings import warn
 import torch
 import numpy as np
 
+
 class Compose(object):
     """Composes several transforms together.
 
@@ -150,6 +152,11 @@ class LC2CL(object):
         return self.__class__.__name__ + '()'
 
 
+def SPECTROGRAM(*args, **kwargs):
+    warn("SPECTROGRAM has been renamed to Spectrogram")
+    return Spectrogram(*args, **kwargs)
+
+
 class Spectrogram(object):
     """Create a spectrogram from a raw audio signal
 
@@ -200,6 +207,11 @@ class Spectrogram(object):
         return spec_f
 
 
+def F2M(*args, **kwargs):
+    warn("F2M has been renamed to MelScale")
+    return MelScale(*args, **kwargs)
+
+
 class MelScale(object):
     """This turns a normal STFT into a mel frequency STFT, using a conversion
        matrix.  This uses triangular filter banks.
@@ -256,6 +268,11 @@ class MelScale(object):
         return 700. * (10**(mel / 2595.) - 1.)
 
 
+def SPEC2DB(*args, **kwargs):
+    warn("SPEC2DB has been renamed to SpectogramToDB, please update your program")
+    return SpectogramToDB(*args, **kwargs)
+
+
 class SpectogramToDB(object):
     """Turns a spectrogram from the power/amplitude scale to the decibel scale.
 
@@ -276,10 +293,15 @@ class SpectogramToDB(object):
 
         spec_db = self.multiplier * torch.log10(spec / spec.max())  # power -> dB
         if self.top_db is not None:
-            spec_db = torch.max(spec_db, spec_db.new_full((1,),self.top_db))
+            spec_db = torch.max(spec_db, spec_db.new_full((1,), self.top_db))
         return spec_db
 
 
+def MEL2(*args, **kwargs):
+    warn("MEL2 has been renamed to MelSpectrogram")
+    return MelSpectrogram(*args, **kwargs)
+
+
 class MelSpectrogram(object):
     """Create MEL Spectrograms from a raw audio signal using the stft
        function in PyTorch.
@@ -341,6 +363,11 @@ class MelSpectrogram(object):
 
         return spec_mel_db
 
+
+def MEL(*args, **kwargs):
+    raise DeprecationWarning("MEL has been removed from the library please use MelSpectrogram or librosa")
+
+
 class BLC2CBL(object):
     """Permute a 3d tensor from Bands x Sample length x Channels to Channels x
        Bands x Samples length